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Changement de régime dans le
réseau alimentaire du bank
Georges et rétablissement des
stocks de poissons
surexploités
Jeremy Collie
Graduate School of Oceanography
University of Rhode Island
[email protected]
22 May 2017
8e Forum haliemétrique
1
Sommaire
 Changements à long terme dans les communautes
de poissions, causes par l’exploitation et le climat;
 La variation climatique éffectue des changements
dans le réseau alimentaire;
 Example: ecosystème du banc Georges;
• Modèle du réseau alimentaire linéaire;
• Modèle biomass-dynamique plurispécifique;
• Modèle structuré d’après l’âge plurispécifique;
• Modèle multi-équilibre;
• La dynamique mono-spécifique de l’églefin.
 Conclusions génerales
Gradient
Gradientof
ofModel
Model Complexity
Complexity
Single-species
Multi-species
Aggregate
Ecosystem
Gadids
Flatfish
Single-species
models: useful for
stock assessment
and management;
Can add explicit
predators, habitat
or climate
considerations.
Pelagics
Age structured
multispecies
assessments;
Food-web or
energy-budget
models;
Multispecies
production
models.
May be massbalance or
dynamic.
Whole
Ecosystem
Messy
Picture
Here
Whole
ecosystem
models:
forget
population
dynamics.
Modified from Link (2002) Fisheries 27:18-21
Example: Georges Bank Ecosystem
Image from Peter Wiebe (2002) Oceanography 15:14.
22 May 2017
8e Forum haliemétrique
4
Piscivorous
fish
Juvenile
fish
Benthivorous
fish
Planktivorous
fish
Carnivorous
benthos
Suspension
feeders
Carnivorous
plankton
Deposit
feeders
Mesozooplankton
Feces
Loss
Detritus
Microzooplankton
Loss
Loss
Small phytoplankton
Loss
Large phytoplankton
NO
Ammonia
3
Loss
(a) Mesozooplankton
15
10
Spatial zones
5
0
Fall/Winter
Spring
Summer
Production (gC m-2)
(b) Suspension feeding benthos
5
Stratified
Transition
Mixed
4
3
2
1
0
Fall/Winter
Spring
Summer
(c) Deposit feeding benthos
4
Zooplankton 27.0
3
Benthos
2
1
0
Integrated
production
(gC m-2 yr-1)
Fall/Winter
Spring
Season
Summer
10.5
Piscivorous
fish
Juvenile
fish
Benthivorous
fish
Planktivorous
fish
Carnivorous
benthos
Suspension
feeders
Carnivorous
plankton
Deposit
feeders
Mesozooplankton
Feces
Loss
Detritus
Microzooplankton
Loss
Loss
Small phytoplankton
Loss
Large phytoplankton
NO
Ammonia
3
Loss
(a) Planktivores
50
40
Other
30
Herring
Butterfish
20
Mackerel
10
Sand lance
0
1965
1970
1975
1980
1985
1990
1995
2000
(b) Piscivores
Biomass (g m-2)
25
Other
20
Silver hake
15
Pollock
10
Cod
Spiny dogfish
5
0
Winter skate
1965
1970
1975
1980
1985
1990
1995
2000
(c) Benthivores
15
Other
Yellowtail flounder
10
Little skate
Longhorn sculpin
5
Haddock
Ocean pout
0
1965
1970
1975
1980
1985
Year
1990
1995
2000
Data from Stockhausen, NMFS
Biomass of Predator Guilds
Biomass
3
Planktivores
Piscivores
Benthivores
2
1
0
Consumption by Predator Guilds
Consumption
10
Plankton
Fish
5
Benthos
0
Consumption by Prey Source
Consumption
15
Plankton
Benthos
10
5
0
1963-1972
1973-1982
1983-1992
Stanza
1993-2002
Balancing the upper and lower food webs
Fish
Feeders
Four Stanzas:
1963-2002
Benthos
Feeders
Plankton
Feeders
Carnivorous
benthos
Carnivorous
plankton
Benthos
Plankton
Lower Web
GLOBEC:
1995-1999
Fish consumption accounts for all the
production from the lower food web
Plankton
gC m-2 yr-1
30
20
Carnivorous plankton
Fish
Unconsumed
10
0
Benthos
gC m-2 yr-1
15
10
Carnivorous benthos
Fish
Unconsumed
5
0
Production from lower
food web
63-7273-82 83-9293-02
Stanza
Low Nitrate
Steele, Collie, Gifford, et al. (In press)
Conclusions from the food webs
The lower food web accounts for recycling, spatial
and seasonal differences, and advective losses;
Commercially-important species have been
replaced with non-commercial species;
Plankton consumption has increased relative to
benthos;
There is some evidence of bottom-up control of
fish production in the 1960s;
Outputs from the lower food web limit fish
production;
Therefore, recovery of the commercial fish species
requires reductions in non-commercial species.
0.8
Is there enough food for a recovered
cod stock?
0.2
0
100
1960s 1970s 1980s 1990s 2004
Survey
2007
2008
Targets
2009
Bmsy
Binf
Reference levels
Production (gC m-2 yr-1)
0.4
300
200
 8.8
0
Biomass (kt)
400
0.6
500
 21
Food-web modifications
J.H. Steele (Personal Communication)
(a)
Individual change
x 1.8
2.8
1.6
1.4
1.2
x 2.0
1
0.8
0.6
0.4
0.2
No Change
0
Factor Inc.
st
d
r
m un
aj
Pi
s
no c
IC
no Z
I
m CB
or
eS
le B
ss
m Mz
in
D
et
r
I II III IV V VI VII
Cumulative change
(b)
4
3.5
-2
-1
gC.m
gC.m-2.year
.year-1
Scenarios:
I.
Make cod the dominant species
in the piscivore guild;
II. Make piscivores the dominant
guild;
III. Eliminate carnivorous
zooplankton (jellyfish);
IV. Eliminate carnivorous benthos;
V. Increase suspension-feeding
benthos;
VI. Reduce microzooplankton;
VII. Reduce flux of phytoplankton
to the benthos.
3
2.5
Plank
Benth
Pisc
2
1.5
1
Binf
Bmsy
0.5
0
init.
Cod
std maj no
no more less min
run Pisc ICZ ICB SB Mz Detr
Multispecies production models of the
Georges Bank fish community
Model Formulation (gadoids as example):
r 2
Gt 1  Gt  rGt 1  Gt 1  Yt  species interaction terms
k
Competition (negative)
cgeGt 1Et 1
Predation (positive or negative)
Type I
dgpGt 1Pt 1
22 May 2017
Type II
Type III
d gpGt 1Pt 1
d gpGt 1Pt21
1  agf F8t Forum
agp Pt 1
1 haliemétrique
2
1  agf Ft21  agp P
15t 1
e
Simplified Georges Bank Food Web
gadoids
+ Type III
interactions
-
Type I
interactions
flatfish
-
-
pelagics
elasmobranchs
+
Collie and DeLong (1999)
Single and multispecies model fits
1200
Gadoids
1000
800
600
.
observed
single-species
muti-species
yield
80
70
60
50
40
30
20
10
0
1964
400
200
0
1964
1969
1974
1979
1984
1989
700
600
Flatfish
1969
1974
1979
1984
1989
250
Pelagics
200
Elasmobranchs
500
400
150
300
100
200
50
100
0
1964
1969
1974
1979
1984
0
1964
1989
Year
1969
1974
1979
1984
1989
Gadoids
1200
.
1000
800
600
observed
model fit
yield
positive effect of pelagics
competition with elasmobranchs
400
200
0
1964
1969
1974
1979
Year
1984
1989
Gadoid equilibrium yield depends on
the harvest rates of the other groups
hmsy
0.5
0.3
0.2
hmsy
0.1
0.0
0.2
0.4
Gadoid harvest rate
0.0
0.6
Pelagic harvest rate
0.4
90-105
75-90
60-75
45-60
30-45
15-30
0-15
Conclusions from multispecies
production models
Multispecies production models can be fit
statistically to time series of abundance data;
In this example the multispecies models fit
significantly better than single-species models;
Gadoids and elasmobranchs compete with each
other and prey on pelagics and flatfish;
Trade-offs exist between predator and prey
yields (May et al. 1979);
Biological reference points depend on the
abundances of other taxa (Collie & Gislasson
2001).
Multispecies Virtual Population Analysis
of the Georges Bank fish community
silver hake
winter skate
sand lance
haddock
herring
female dogfish
male dogfish
yellowtail flounder
cod
mackerel
Tsou & Collie (2001a)
catchat-age
diet
composition
other
food
M&
weight consumption
terminal
at age
rates
Fs
MSVPA
estimation of suitability coefficients
fishing
mortality
stock
numbers
suitability
coefficients
from Per Sparre (1991)
predation
mortality
Predation mortality rates are high
1.8
Predation mortality
1.6
Age 0
Age 1
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
cod
silver hake haddock
mackerel
herring
yellowtail
flounder
Prey species
Tsou & Collie (2001b)
Biomass of prey consumed by year and predator
1981
1984
1987
4
0
2
Biomass consumed (kt)
6
8
400
300
200
Biomass consumed (kt)
haddock
100
1990
1978
1981
1984
1987
1990
1978
1981
1984
1987
1990
Year
Year
mackerel
herring
yellowtail flounder
221978
May 1981
20171984
Year
1987
1990
4
3
0
0
0
1
2
Biomass consumed (kt)
150
100
Biomass consumed (kt)
50
6
4
2
5
200
Year
8
1978
Biomass consumed (kt)
silver hake
0
5
10
wsk
mdg
fdg
had
shk
cod
0
Biomass consumed (kt)
15
cod
8e Forum
haliemétrique
1981
1984 1987
1990
1978
Year
1978
1981
1984
Year
1987
1990
24
Total prey biomass over time
1400
1200
b
Biomass (kt)
1000
ytf
her
800
mck
had
600
shk
cod
400
200
0
1978
1981
1984
1987
1990
Year
22 May 2017
8e Forum haliemétrique
25
0.4
0.6
0.8
1978
1981
1984
Year
1987
1990
1978
1981
1984
1984
Year
1987
Year
Year
female dogfish
male dogfish
winter skate
1987
1990
1.0
1981
0.8
1978
0.6
0.0
0.4
0.6
0.8
0.4
0.6
0.8
0.2
0.4
0.6
0.8
Proportion of biomass consumed
0.2
Proportion of biomass consumed
0.2
Proportion of biomass consumed
1.0
1.0
1.0
silver hake
0.4
0.0
0.0
cod
0.2
Year
1.0
1990
Proportion of biomass consumed
0.8
1987
0.6
1984
0.4
1.0
1981
0.2
Proportion of biomass consumed
0.2
Proportion of biomass consumed
1978
0.0
0.0
0.0
Species composition of the diet of six predators
1990
haddock
ytf
her
mck
had
shk
cod
1978
1978
1981
1981
1984
1984
Year
1987
1987
1990
1990
Predation affects year-class size for some species
Preda1t.i0onmrlty 2.0
Age-1abundce(mil0ons) 20 40
Silver hake
1979
01 0
20
0
3
0
0
0
0
0
0
0
0
0
1
0
0
20
0
3
0
0
0
0
0
00
0
a
A
b
g
u
e
n
d
0
a
a
P1.0redationmrlty 1.5 2.0 2.5
A g e -0
Age-2abundce(milo1n0s) 30 50
1986
10
20
30
40 0
1
0
0
20
30
40 0
A g e -1
a
A
b
g
u
e
n
d
1
a
a
Regimes shifts can be illustrated with a
catastrophe manifold
Points on the
manifold represent
equilibrium values of
the “fast” variable
(Abundance) for
possible
combinations of the
“slow” variables,
Internal Structure
and External Forcing
Collie, Steele, and Richardson (2004)
Simple models can have multiple
equilibria
0
0
1
2
C. Three Equilibria
2
B. Two Equilibria
1
2
1
0
5
10
15
20
25
30
n=2
-2
-2
-1
n=1
-1
0
-1
c=0
-2
Population growth rate
A. Single Equilibrium
0
5
10
15
20
25
30
Population size
dP
Pn
 P
 rP 1    cH n
dt
D  Pn
 K
P population abundance
r rate of increase
K carrying capacity
0
5
10
15
20
25
30
Stable equilibrium
Unstable equilibrium
c consumption rate of predator H
n exponent of functional response
D half-saturation constant
Criteria for distinguishing regime shifts
A. Shift in time series
D. Trajectory depends
on initial state
B. Bimodal distribution
E. Triggered shift
C. Dual relationship
F. Hysteresis
Scheffer and Carpenter (2003)
Example: Georges Bank haddock
Haddock was the most
abundant demersal fish
species from 1930-1965
H. L. Todd, Illustrator
Overfished in the 1960s,
the stock is now
recovering dramatically.
Photo by Howard Schuck (1953) NEFSC Photo archive
Georges Bank Haddock
C. Dual relationship
2000
100
Year
Year
60
400
0.0
40
60
Time (years)
80 100
60
80
0.0
20
0.6
40
0.4
0.2
300
0
0.4
F. Hysteresis
Fishing mortality
500
2000
0.2
Fishing mortality
0 100
Biomass (kt)
4
2
0
Lisbon-Iceland
-2
-4
1980
300
E. Triggered shift
Winter NAO
1960
200
Biomass
D. Forcing variable
1940
40
0
0
20
1980
0
1960
Catch (kt)
1940
2004
20
Catch (kt)
10
5
0
Frequency
300
100
0
Thousand tonnes
Biomass
Catch
1931-1968
1969-2004
80
B. Biomodality
15
A. Regime Shift
0.0
0.2
0.4
Fishing mortality
0.6
Implications for rebuilding
depleted stocks
Yields are restricted by the
climatic regime, or …
?
… the stock can rebuild to
prior high abundance.
Why do some fish stocks recover …
70
500
Haddock
400
Atlantic cod
Yellowtail flounder
60
50
40
300
30
200
20
100
10
0
Yellowtail Flounder Biomass (kt)
Haddock and Cod Biomass (kt)
600
0
1963 1967 1971 1975 1979 1983 1987 1991 1995 1999 2003
Year
… while others don’t?
Control Rule for Georges Bank Haddock
3.5
Bmsy
Relative Fishing Mortality
3.0
Equilibrium
Trajectory
2.5
2.0
1967
1.5
1.0
Fmsy
0.5
2000
0.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Relative Spawning Stock Biomass (kt)
22 May 2017
8e Forum haliemétrique
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General Conclusions
Bottom-up forcing of marine food webs alters
community structure and fish productivity;
Strong trophic interactions imply trade-offs in
fisheries yields;
Fishing can induce regime shifts and delay
the recovery from climate-driven shifts;
Single-species are assessed and managed
within this ecological milieu;
Fish stocks can recover from overexploitation,
if management sets the stage.
22 May 2017
8e Forum haliemétrique
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Acknowledgements
Collaborators:
John Steele
Michael Fogarty
Jason Link
Allison DeLong
Tien-shui Tsou
Dian Gifford
22 May 2017
Russell
Brown
Funding Agencies:
National Science
Foundation
Rhode Island
Sea Grant
NOAA Coastal Ocean
Program
8 Forum haliemétrique
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